Quantum Moves

featured in

Nature

The article published in the prestigious science journal summarises the results of a study completed by ScienceAtHome on players of Quantum Moves, our flagship game.

The article published in Nature summarises the results of a study we completed on the players of Quantum Moves, our flagship game. The study focuses on a single level called BringHomeWater, the perfect example of a complex problem—very hard for computers, and a real challenge for a dedicated player! Over 150 thousand players have taken up this challenge, playing BringHomeWater a whopping 8 million times. Talk about dedication!

While playing BringHomeWater persistently, our players have helped us find clever solutions to very interesting quantum physics problems. BringHomeWater is about moving an optical tweezer (a laser beam in the physics lab and the empty well players move in the game) over to a trapped atom (in the lab atoms are trapped with lasers while in the game the trapped atom is a second well with some sloshy liquid inside it) picking up the atom and moving it to the target area.

We are interested in moving single atoms around for two reasons:

1

Moving atoms is tricky! Single atoms are hard to trap and even more difficult to move. This is why a player sees so much sloshing of the liquid in the game—it very directly reflects the difficulty of keeping the atom stable.

2

Atoms need to be moved on top of each other so that they can interact. If we cannot do this, we have a design for a quantum computer that sits still and does nothing! To run operations, atoms need to be moved around so that they can “talk” to each other.

So this is the core problem we study: how do I move an atom? There are many possible solutions to this problem—it’s always possible to find some path—but the hard thing is finding the best way to move the atom. We want to find the best solution, so we need to optimize the way the atom is moved.

When we asked a whole lot of computer algorithms to solve the problem, they did find a lot of solutions. The problem is that the solutions are not very good. To be more precise, the solutions found by the computer are typically very slow. (We need fast solutions to make the computations fast and to avoid external noise from making our atoms slosh even more.) Computer algorithms are just not very smart as finding fast solutions, as they are too focused on getting the solutions to be perfect. (Perfect in this case means that the atom is stable after it has been moved to the target area. In the game this means that there is no or very little sloshing in the end.)

When players play the game, they go about the problem much more intuitively. A computer tries to do all sorts of stupid things, but a human knows immediately what makes sense. When we looked at the 8 million plays from our players, we found out that humans are good at finding solutions that are fast. (We encouraged people to find a fast solution by having a time limit for the gameplay.)

The catch is that fast solutions found by humans are not that good—there is often still a fair bit of sloshing in the end. However, when we have a good idea from the humans, we can feed this idea into the computer—that does not come up with smart ideas itself—and then the computer can refine the solution so that eventually we have solutions that are fast and good.

The best solutions we found this way are much better than any previous studies indicated. This is one of our main results for physicists. (The expression Quantum Speed Limit in the title of the article refers exactly to this. The speed limit defines the shortest time for finding good, stable solutions. We found a new quantum speed limit which is smaller than any limit found before for this problem. The Quantum Speed Limit sets the ultimate bounds for a quantum computer, so it’s very important to have it as short as possible!)

One of the most important results in a more general sense is that human input was crucial in finding these solutions. Humans alone are not perfect, computers alone are not perfect, but humans and computers TOGETHER are pretty powerful at solving immensely difficult problems!

When analysing the player solutions further we found that players use two dominant strategies for solving the problem. These correspond to two different physical mechanisms that use high-level quantum physics. It’s pretty amazing that people who possibly know nothing about quantum physics are able to come up with two different ways of solving the problem. This goes to show that imagination is the only limit for using non-trained people to help scientists solve real science problems!

What are some of the consequences of our work?

– We showed that humans are very good at solving quantum problems. This was unexpected because people have no intuition on how quantum objects work—quantum phenomena is simply not a part of our everyday experiences!

– This project has shown once more that people with no scientific training can still make a significant contribution to the mysteries of nature. Long training is not always the way to go, sometimes it’s much better to think outside of the box.

– We are one step closer to a functional quantum computer. And not just any version of this elusive machine, but a quantum computer that could have around 300 quantum bits. This is much more than other proposals for quantum computers! We are not there yet, but a bit closer to having the ultimate supercomputer…

How your gameplay helps ScienceAtHome build a quantum computer

What are quantum computers and how goes playing games help physicists in cutting edge research? Take a look at our stop motion film that explains how playing our games can help our research.